Value Chain Innovation Dimension Overview
FUTUR-IC seeks to optimize the competitiveness, resource efficiency, and health impacts of the value chains that provide the materials and component technology required for high performance microchip systems.
A holistic value chain approach can advance technological development and predict the impacts of future innovations. FUTUR-IC leverages tools to deliver value chain intelligence as well as identify resource hotspots and bottlenecks in electronic materials and manufacturing processes. To build a robust domestic value chain for increased national security, FUTUR-IC creates data analytics to assess the impacts of using electricity, water, materials, etc., in the microchip industry by establishing consensus on figures of merit that can optimize resource efficiency despite geopolitical constraints. It also generates data-driven insights to inform a comprehensive microchip technology roadmap.
Realtime Automatic Feedback on Value Chain Models
Optimization of value chains requires the construction of value chain process models, including modelling foreground processes and linking to appropriate datasets in professional background databases and from suppliers. Three decades of experience helping professionals advance value chain model-building has demonstrated that modelers need feedback on their model-building.
Current demand for such model-building feedback and guidance exceeds the supply, and there is a need to further scale modelling capabilities. Such scaling requires scaling the ability of enable hands-on model refinement experience.
A major hurdle to such scaling is the challenge of getting model builders timely and detailed feedback on their modelling efforts and progress. Providing such feedback taxes the time availability of available experts; limited ability to provide such feedback can reduce the willingness of designers and practitioners to include hands-on model-building in their value chain optimization at all.
The VCI dimension team has developed and now makes freely available a set of algorithms that provide real-time automatic feedback on the value chain models as they are being built. The functionality can dramatically reduce the time that experts spend trying to identify problems or errors in their colleagues’ models, enabling experts to focus their feedback and speed the task of value chain optimization for resource efficiency.
Critical Materials Assessment for Semiconductors
The product of today’s high-performance semiconductors and digital systems currently makes extensive use of rare metals and other strategic materials and components that can only be sourced from a few countries. Such materials are referred to as “critical materials.” Reliance on critical materials can pose security and competitiveness risks for the industry and for the country as well.
Design choices properly informed by research and tools being advanced by the VCI Dimension of FUTUR-IC may enable photonics solutions to offer measurably improved (that is, reduced) critical materials risk compared with today’s digital system solutions. In collaboration with TechInsights, our researchers have obtained proprietary data on the inputs to manufacture five different technologies on the wafer level and across a range of legacy to novel node sizes for analysis.
Results of the assessment so far indicate that rapid upscale of domestic US semiconductor manufacturing may experience bottle necks in multiple materials integral to production. The next step in the research is to use advanced evaluation systems that widen the field of factors and pathways assessed for their influence on material criticality.
2024 USGS production (and, where reported, refinement) estimates for semiconductor manufacturing inputs against U.S. State-Department geopolitical designations. Overall, roughly half of the listed commodities have >50 % of their supply rooted in regions the United States classifies as “adversary” elevating both trade-disruption and ESG-compliance risks for chipmakers. By contrast, U.S. domestic output is negligible or unreported for all but two elements, highlighting the strategic gap between critical materials availability and current industrial aspirations for a rapid upscale of domestic manufacturing capacity. These findings reinforce the urgency of diversification strategies—whether via allied sourcing, circular recovery, or accelerated domestic refining capacity—to secure resilient semiconductor supply chains in the face of mounting geopolitical volatility. Thirteen of the materials are already majority-sourced from a single nation, underscoring acute supply-side concentration. When downstream refining is considered, this dominance intensifies—several elements that appear geographically diversified at the mine mouth become even more tightly clustered within one jurisdiction’s processing sector.
How PAIA can streamline your organization’s footprint assessment needs in digital technology and ICs
The Product Attributes to Impact Algorithm (PAIA) is a fast-track calculator that turns lengthy, resource-heavy product footprint studies into quick, repeatable look-ups.
Designed for ICT, hardware, and network gear alike, the tool draws on an up-to-date data library and smart defaults, so ICT teams can:
- Publish credible footprint figures in days, not months.
- Keep pace with every version refresh—no starting from scratch.
- Compare results across product lines on a single, consistent scale.
If you juggle dozens (or hundreds) of SKUs and need solid numbers before the next release cycle, PAIA puts streamlined, side-by-side impact tracking at your fingertips.
Resources
GenTronics Phone Supply Chain Game
Advances in waveguide to waveguide couplers for 3D integrated photonic packaging
Graded index couplers for next generation chip-to-chip andfiber-to-chip photonic packaging
High density vertical optical interconnects for passive assembly
Hands-On Photonic Education Kits: empowering the integrated photonics workforce through practical training
